1.最短路(Floyd、Dijstra,BellmanFord) 2.最小生成树(先写个prim,kruscal要用并查集,不好写) 3.大数(高精度)加减乘除 4.二分查找. (代码可在五行以内) 5.叉乘、判线段相交、然后写个凸包. 6.BFS、DFS,同时熟练hash表(要熟,要灵活,代码要简) 7.数学上的有:辗转相除(两行内),线段交点、多角形面积公式...
It's John Sonmez from simpleprogrammer.com. I have a question here that a lot of people have been asking lately since I did this video on “Do I need to learn algorithms?” Now, the question is “How to learn algorithms?” Obviously, that was—I must have known that was coming. Thi...
Months 4-6: Learn core AI concepts, including machine learning algorithms, model building, and deep learning basics. Months 7-9: Specialize in areas like NLP, computer vision, or AI for business. Work on real-world projects. Months 10+: Keep improving! Follow AI research, contribute to proj...
But there's growing research that pricing algorithms themselves could learn to form a kind of digital cartel of their own… and collude to raise prices without any human involvement. Joseph Harrington:Now, well let's think about a manager deciding that they're going to delegate the pricing dec...
You can’t use machine learning unless you know how to program. Luckily, we have a free guide:How to Learn Python for Data Science, The Self-Starter Way Statistics for Data Science Statistics, especially Bayesian probability, underpins many ML algorithms. We have a free guide:How to Learn ...
Because of this discovery, it is possible than even faster algorithms will be discovered. It is therefore natural to ask: did fast human calculators of the past use faster algorithms – in which case we can learn from their experience – or they simply performed all operations within a ...
We don’t know what the function (f) looks like or it’s form. If we did, we would use it directly and we would not need to learn it from data using machine learning algorithms. It is harder than you think. There is also error (e) that is independent of the input data (X). ...
A sequence of moves is often referred to as an “algorithm” by cube enthusiasts. The sought-after Rubik’s Cube algorithms are those that move just a few of the cubies while leaving the rest untouched. The limitations to the algorithms are the key to that number 12. Can You Solve It?
In supervised learning, training means using historical data to build a machine learning model that minimizes errors. The number of minutes or hours necessary to train a model varies a great deal between algorithms. Training time is often closely tied to accuracy; one typically accompanies the othe...
And then, some 10 years ago, when the number of malware samples grew to surpass any previously imagined levels, machine-learning algorithms started slowly to find their way into antivirus programs. At first, in terms of complexity they did not stretch too far beyond the primitive algorithm we...